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Bump lightgbm from 4.5.0 to 4.6.0 in /numerai/examples/signals-python3 - #105

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Bumps lightgbm from 4.5.0 to 4.6.0.

Release notes

Sourced from lightgbm's releases.

v4.6.0

Changes

💡 New Features

🔨 Breaking

  • [R-package] require lgb.Dataset, remove support for passing 'colnames' and 'categorical_feature' for lgb.train() and lgb.cv() @​jameslamb (#6714)
  • [python-package] support sub-classing scikit-learn estimators @​jameslamb (#6783)
  • [python-package] do not copy column-major numpy arrays when creating Dataset from list of arrays @​jmoralez (#6773)
  • [python-package] remove support for passing 'feature_name' and 'categorical_feature' through train() and cv() @​jameslamb (#6706)
  • [python-package] require scikit-learn>=0.24.2, make scikit-learn estimators compatible with scikit-learn>=1.6.0dev @​vnherdeiro (#6651)
  • [ci] Require CMake 3.28 and replace FetchContent_Populate with FetchContent_MakeAvailable @​StrikerRUS (#6550)

🚀 Efficiency Improvement

  • [python-package] do not copy column-major numpy arrays when predicting @​jmoralez (#6751)
  • [python-package] do not copy column-major numpy arrays when creating Dataset @​jmoralez (#6721)

🐛 Bug Fixes

  • [python-package] Separately check whether pyarrow and cffi are installed @​mlondschien (#6785)
  • [c++] Fixed Predictor lifecycle and trees initialization in Contrib mode @​AndreyOrb (#6778)
  • [python-package] Infer feature names from pyarrow.Table @​mlondschien (#6781)
  • [python-package] Fix inconsistency in predict() output shape for 1-tree models @​RektPunk (#6753)
  • [fix] resolve potential attack in linker connection building @​shiyu1994 (#6752)
  • [R-package] Avoid bashisms (non-POSIX code) in R-package/configure @​smoser (#6746)
  • [c++] fix parallel_tree_learner_split_info @​moming39 (#6738)
  • [c++] Fix dump_model() information for root node @​neNasko1 (#6569)
  • [cmake] [R-package] include R-for-macOS vendored libs dir in OpenMP search path (fixes #6628) @​jameslamb (#6629)
  • [R-package] only warn about early stopping and DART boosting being incompatible if early stopping was requested @​serkor1 (#6619)
  • [cmake] fixes static build for macos with OpenMP enabled (fixes #6601) @​Mottl (#6600)

📖 Documentation

... (truncated)

Commits
  • d02a01a release v4.6.0 (#6796)
  • d24260f [R-package] require lgb.Dataset, remove support for passing 'colnames' and 'c...
  • c6d90bc [python-package] support sub-classing scikit-learn estimators (#6783)
  • 768f642 [c++] update to fmt 11.1.2, fast_double_parser 0.8.0 (#6802)
  • 1531d87 [ci] fix valgrind workflow (#6816)
  • 188f1be [ci] validate pyproject file by json schema (#6813)
  • 81922a7 [ci] [python-package] update pre-commit hooks to latest versions (#6817)
  • 2db0b25 [python-package] Separately check whether pyarrow and cffi are installed ...
  • c9de57b [CUDA] fix setting of CUDA architectures and enable support for NVIDIA Blackw...
  • f2b959c [ci]: Bump release-drafter/release-drafter from 6.0.0 to 6.1.0 in the ci-depe...
  • Additional commits viewable in compare view

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Bumps [lightgbm](https://github.com/lightgbm-org/LightGBM) from 4.5.0 to 4.6.0.
- [Release notes](https://github.com/lightgbm-org/LightGBM/releases)
- [Commits](lightgbm-org/LightGBM@v4.5.0...v4.6.0)

---
updated-dependencies:
- dependency-name: lightgbm
  dependency-version: 4.6.0
  dependency-type: direct:production
...

Signed-off-by: dependabot[bot] <support@github.com>
@dependabot dependabot Bot added dependencies Pull requests that update a dependency file python Pull requests that update python code labels Sep 30, 2026

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Looks good, straightforward dependency version bump.

What was reviewed: the single-line change bumping lightgbm from 4.5.0 to 4.6.0 in numerai/examples/signals-python3/requirements.txt. Checked lightgbm's 4.6.0 release notes for breaking changes affecting this example - the listed breaking changes are R-package, scikit-learn subclassing, and column-major array handling, none of which affect this basic train/predict usage. Considered pickle/joblib model compatibility across the version bump - this only affects existing users' saved models, not correctness of this repo's code.

Extended reasoning...

Single-line dependabot version bump in an example requirements.txt, no source code or logic changes. No security-sensitive surface (auth, crypto, permissions) is touched. Change is simple and mechanical, matching the approval guideline for version bumps.

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